Enhanced collision mitigation

ABSTRACT

A computer includes a processor and a memory, the memory storing instructions executable by the processor to, upon determining that a yaw rate for a host vehicle is below a threshold, identify a front corner point of a target, and to suppress threat mitigation when a time to collision between the host vehicle and front corner point of the target exceeds a time threshold.

BACKGROUND

Vehicle collisions often occur at intersections. Collision mitigationbetween a host vehicle and a target vehicle or other object may bedifficult and expensive to implement. For example, determining a threatassessment for the target may use limited or inaccurate data to assignexcessive risk to a scenario that in fact may not require avoidance ormitigation. Furthermore, performing the threat assessment may result inpositive identifications of threat that may not require mitigation,which can be operationally costly for a vehicle computer and vehiclecomponents, increasing consumption of processing resources of thevehicle computer to perform the threat assessment and actuate thevehicle components.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an example system for operating a vehicle.

FIG. 2 is a plan view of the vehicle and an example target.

FIG. 3 is a plan view of the vehicle and a front corner point of theexample target.

FIG. 4 is a diagram of an example process for operating the vehicle.

DETAILED DESCRIPTION

A system includes a computer including a processor and a memory, thememory storing instructions executable by the processor to, upondetermining that a yaw rate for a host vehicle is below a threshold,identify a front corner point of a target, and suppress threatmitigation when a time to collision between the host vehicle and frontcorner point of the target exceeds a time threshold.

The instructions can further include instructions to identify the frontcorner point as a closest corner point of the target to the hostvehicle.

The instructions can further include instructions to determine the timeto collision between a front center point of the host vehicle and thefront corner point of the target.

The instructions can further include instructions to determine a threatnumber based on a front center point of the host vehicle and a frontcenter point of the target.

The instructions can further include instructions to determine thethreat number based on a center time to collision between the frontcenter point of the host vehicle and the front center point of thetarget.

The instructions can further include instructions to actuate a componentbased on a threat number.

The instructions can further include instructions to, upon determiningthat the threat number exceeds a threat threshold, determine whether theyaw rate is below the threshold.

The instructions can further include instructions to multiply a threatmultiplier to the threat number to suppress the threat mitigation.

The instructions can further include instructions to set the threatmultiplier to zero when the time to collision exceeds the timethreshold.

The instructions can further include instructions to actuate a brakewhen the time to collision is below the time threshold.

The instructions can further include instructions to identify the frontcorner point of the target based on a lateral width of the target.

The instructions to suppress threat mitigation can further includeinstructions to suppress actuation of a brake.

The instructions can further include instructions to determine whetherthe host vehicle is in a turn based on a sign of the yaw rate.

The instructions can further include instructions to suppress threatmitigation when the sign of the yaw rate is negative.

A method includes upon determining that a yaw rate for a host vehicle isbelow a threshold, identifying a front corner point of a target andsuppressing threat mitigation when a time to collision between the hostvehicle and front corner point of the target exceeds a time threshold.

The method can further include identifying the front corner point as aclosest corner point of the target to the host vehicle.

The method can further include determining the time to collision betweena front center point of the host vehicle and the front corner point ofthe target.

The method can further include determining a threat number based on afront center point of the host vehicle and a front center point of thetarget.

The method can further include determining the threat number based on acenter time to collision between the front center point of the hostvehicle and the front center point of the target.

The method can further include actuating a component based on a threatnumber.

The method can further include, upon determining that the threat numberexceeds a threat threshold, determining whether the yaw rate is belowthe threshold.

The method can further include multiplying a threat multiplier to thethreat number to suppress the threat mitigation.

The method can further include setting the threat multiplier to zerowhen the time to collision exceeds the time threshold.

The method can further include actuating a brake when the time tocollision is below the time threshold.

The method can further include identifying the front corner point of thetarget based on a lateral width of the target.

The method can further include suppressing actuation of a brake.

The method can further include determining whether the host vehicle isin a turn based on a sign of the yaw rate.

The method can further include suppressing threat mitigation when thesign of the yaw rate is negative.

A system includes a brake in a host vehicle, means for identifying afront corner point of a target upon determining that a yaw rate for thehost vehicle is below a threshold, and means for suppressing the brakewhen a time to collision between the host vehicle and front corner pointof the target exceeds a time threshold.

The system can further include means for determining the time tocollision between a front center point of the host vehicle and the frontcorner point of the target.

The system can further include means for determining a threat numberbased on a front center point of the host vehicle and a front centerpoint of the target.

Further disclosed is a computing device programmed to execute any of theabove method steps. Yet further disclosed is a vehicle comprising thecomputing device. Yet further disclosed is a computer program product,comprising a computer readable medium storing instructions executable bya computer processor, to execute any of the above method steps.

Upon detecting a target object, a computer in a host vehicle candetermine whether the host vehicle is likely to collide with the target.If a collision is likely, the computer can perform collision avoidanceand/or mitigation. In particular, collisions are likely when the hostvehicle is performing a turn from a current roadway lane to a roadwaylane substantially perpendicular to the current roadway lane, e.g., aleft turn, that crosses a roadway lane in which the target moves towardthe host vehicle. The computer can thus perform collision avoidance andmitigation for targets deemed to be potential threats of collision.

The computer can determine that a threat number of the target exceeds athreshold and perform collision avoidance and/or mitigation. The threatnumber is a unitless measure of whether a specific target will intersector collide with the host vehicle. The computer can determine the threatnumber based on a front center point of a bumper of the host vehicle anda front center point of a bumper of the target.

However, certain host vehicle maneuvers may be similar to a turn but maynot put the host vehicle at risk of a collision with the target. Forexample, when the host vehicle is on a curved roadway, the host vehiclewill turn in order to follow the roadway. The computer may interpret thecurved path to follow the roadway as a turn and, upon detection of atarget in an adjacent lane, perform collision avoidance and mitigationwhere there is no risk of collision. In another example, if the hostvehicle moves from a current lane to an adjacent lane (e.g., a centerturn lane), the computer may interpret the steering to move into theadjacent lane as a turn. These false positive identifications ofcollision avoidance and mitigation can be operationally costly for thecomputer to computationally perform and to actuate the vehiclecomponents, in addition to posing operational and safety risks to thevehicle.

To reduce false positive identifications, upon determining that thethreat number exceeds the threshold, the computer can determine whethera yaw rate of the host vehicle is below a threshold. The threshold canbe determined such that yaw rates below the threshold indicate that thehost vehicle is not likely in a turn and yaw rates above the thresholdindicate that the host vehicle is likely in a turn. For example, thethreshold can be a minimum yaw rate required to complete a turn into aperpendicular roadway lane. If the yaw rate is below the threshold, thecomputer can identify a front corner point of the bumper of the targetand determine a predicted time to collision between the host vehicle andthe front corner point. The front corner point is typically specified tobe the closest point of the target to the host vehicle, so determiningthe time to collision based on the front corner point rather than thefront center point allows the computer to determine more accuratelywhether to perform collision avoidance and/or mitigation.

FIG. 1 illustrates an example system 100 for operating a vehicle 101.The system 100 includes a computer 105. The computer 105, typicallyincluded in a vehicle 101, is programmed to receive collected data 115from one or more sensors 110. For example, vehicle 101 data 115 mayinclude a location of the vehicle 101, data about an environment arounda vehicle 101, data about an object outside the vehicle such as anothervehicle, etc. A vehicle 101 location is typically provided in aconventional form, e.g., geo-coordinates such as latitude and longitudecoordinates obtained via a navigation system that uses the GlobalPositioning System (GPS). Further examples of data 115 can includemeasurements of vehicle 101 systems and components, e.g., a vehicle 101velocity, a vehicle 101 trajectory, etc.

The computer 105 is generally programmed for communications on a vehicle101 network, e.g., including a conventional vehicle 101 communicationsbus. Via the network, bus, and/or other wired or wireless mechanisms(e.g., a wired or wireless local area network in the vehicle 101), thecomputer 105 may transmit messages to various devices in a vehicle 101and/or receive messages from the various devices, e.g., controllers,actuators, sensors, etc., including sensors 110. Alternatively oradditionally, in cases where the computer 105 actually comprisesmultiple devices, the vehicle network may be used for communicationsbetween devices represented as the computer 105 in this disclosure. Inaddition, the computer 105 may be programmed for communicating with thenetwork 125, which, as described below, may include various wired and/orwireless networking technologies, e.g., cellular, Bluetooth®, Bluetooth®Low Energy (BLE), wired and/or wireless packet networks, etc.

The data store 106 can be of any type, e.g., hard disk drives, solidstate drives, servers, or any volatile or non-volatile media. The datastore 106 can store the collected data 115 sent from the sensors 110.

Sensors 110 can include a variety of devices. For example, variouscontrollers in a vehicle 101 may operate as sensors 110 to provide data115 via the vehicle 101 network or bus, e.g., data 115 relating tovehicle speed, acceleration, position, subsystem and/or componentstatus, etc. Further, other sensors 110 could include cameras, motiondetectors, etc., i.e., sensors 110 to provide data 115 for evaluating aposition of a component, evaluating a slope of a roadway, etc. Thesensors 110 could, without limitation, also include short range radar,long range radar, LIDAR, and/or ultrasonic transducers.

Collected data 115 can include a variety of data collected in a vehicle101. Examples of collected data 115 are provided above, and moreover,data 115 are generally collected using one or more sensors 110, and mayadditionally include data calculated therefrom in the computer 105,and/or at the server 130. In general, collected data 115 may include anydata that may be gathered by the sensors 110 and/or computed from suchdata.

The vehicle 101 can include a plurality of vehicle components 120. Inthis context, each vehicle component 120 includes one or more hardwarecomponents adapted to perform a mechanical function or operation—such asmoving the vehicle 101, slowing or stopping the vehicle 101, steeringthe vehicle 101, etc. Non-limiting examples of components 120 include apropulsion component (that includes, e.g., an internal combustion engineand/or an electric motor, etc.), a transmission component, a steeringcomponent (e.g., that may include one or more of a steering wheel, asteering rack, etc.), a brake component (as described below), a parkassist component, an adaptive cruise control component, an adaptivesteering component, a movable seat, or the like.

When the computer 105 partially or fully operates the vehicle 101, thevehicle 101 is an “autonomous” vehicle 101. For purposes of thisdisclosure, the term “autonomous vehicle” is used to refer to a vehicle101 operating in a fully autonomous mode. A fully autonomous mode isdefined as one in which each of vehicle 101 propulsion (typically via apowertrain including an electric motor and/or internal combustionengine), braking, and steering are controlled by the computer 105. Asemi-autonomous mode is one in which at least one of vehicle 101propulsion (typically via a powertrain including an electric motorand/or internal combustion engine), braking, and steering are controlledat least partly by the computer 105 as opposed to a human operator. In anon-autonomous mode, i.e., a manual mode, the vehicle 101 propulsion,braking, and steering are controlled by the human operator.

The system 100 can further include a network 125 connected to a server130 and a data store 135. The computer 105 can further be programmed tocommunicate with one or more remote sites such as the server 130, viathe network 125, such remote site possibly including a data store 135.The network 125 represents one or more mechanisms by which a vehiclecomputer 105 may communicate with a remote server 130. Accordingly, thenetwork 125 can be one or more of various wired or wirelesscommunication mechanisms, including any desired combination of wired(e.g., cable and fiber) and/or wireless (e.g., cellular, wireless,satellite, microwave, and radio frequency) communication mechanisms andany desired network topology (or topologies when multiple communicationmechanisms are utilized). Exemplary communication networks includewireless communication networks (e.g., using Bluetooth®, Bluetooth® LowEnergy (BLE), IEEE 802.11, vehicle-to-vehicle (V2V) such as DedicatedShort Range Communications (DSRC), etc.), local area networks (LAN)and/or wide area networks (WAN), including the Internet, providing datacommunication services.

FIG. 2 is a plan view of an example vehicle 101 and an example target200. The computer 105 can define a two-dimensional rectangularcoordinate system. The coordinate system defines a longitudinaldirection x and a lateral direction y, and an origin at a point O on acenter point of a front bumper of the host vehicle 101. The longitudinaldirection x is a vehicle-forward direction, i.e., the direction in whicha propulsion 120 moves the vehicle 101 when a steering component 120 isat a neutral position. The lateral direction y is perpendicular to thelongitudinal direction x.

The computer 105 can determine a longitudinal length l and a lateralwidth w for each of the host vehicle 101 and the target 200. Based ondata 115 from one or more sensors 110, the computer 105 can determinethe length l_(h) and the width w_(h) of the host vehicle 101 and thelength l_(tg) and the width w_(tg) of the target 200. As used herein,the subscript “h” refers to the host vehicle 101, and the subscript “tg”refers to the target 200. For example, l_(h) is the length of the hostvehicle 101 and l_(tg) is the length of the target 200. The computer 105can use the lengths l_(h), l_(tg) and the widths w_(h), w_(tg) toidentify coordinate points on the host vehicle 101 and the target 200,e.g., a front center point of a bumper of the target 200, as describedbelow.

The computer 105 can determine a trajectory 205 of the host vehicle 101and a trajectory 210 of the target 200. As used herein, a “trajectory”is a predicted a path of travel. Based on the trajectories 205, 210 ofthe host vehicle 101 and the target 200, the computer 105 can determinea likelihood of a collision.

The computer 105 can determine a range r and a range rate {dot over(r)}. As used herein, a “range” is a distance between two specifiedpoints in the coordinate system, e.g., a point on the host vehicle 101and a point on the target 200. The range rate r is rate of change of therange r, i.e., a measure of change of the range r per unit of time. Thecomputer 105 can determine the range r between the origin O and a frontcenter point 215 of the target 200. The front center point 215 of thetarget 200 can be, e.g., a point substantially at a center of a frontbumper of the target 200 at half the width w_(tg) of the target 200.Based on the range r between the origin O and the front center point 215of the target 200, the computer 105 can determine whether to performthreat mitigation.

The computer 105 can determine a yaw angle ψ and a yaw rate {dot over(ψ)} for the host vehicle 101. The yaw angle ψ is the angle definedbetween the trajectory 205 of the host vehicle 101 and the longitudinalaxis x. The yaw rate {dot over (ψ)} is the rate of change of the yawangle ψ, i.e., a measure of change of the range ψ per unit of time. Thatis, the yaw angle ψ and yaw rate {dot over (ψ)} represent curved motionof the host vehicle 101. The yaw angle ψ and yaw rate {dot over (ψ)} candepend on the specific maneuver that the vehicle 101 is performing. Forexample, if the roadway is curved, the yaw rate {dot over (ψ)} willincrease as the vehicle 101 turns to maintain the vehicle 101 within theroadway lane. In another example, if the vehicle 101 moves from acurrent roadway lane to an adjacent roadway lane (i.e., performs a lanechange), the yaw rate {dot over (ψ)} will increase as the vehicle 101moves laterally into the adjacent roadway lane. In another example, ifthe vehicle 101 is performing a turn from a current roadway lane to aperpendicular roadway lane (e.g., performing a left-hand turn), the yawrate {dot over (ψ)} will increase as the vehicle 101 turns into theperpendicular roadway lane. Typically, the yaw rate {dot over (ψ)}required for a turn into a perpendicular roadway lane is greater thanthe yaw rate {dot over (ψ)} for a curved road or for a lane change.Thus, if the yaw rate ψ is low, as described below, the computer 105 candetermine that the vehicle 101 may not be in a turn (where collisionmitigation may be required) but rather in a lane change or on a curvedroad (where collision mitigation may not be required).

To determine a likelihood of a collision between the host vehicle 101and the target 200, the computer 105 can determine a “threat number” forthe target. As used herein, a “threat number” is a scalar value between0 and 1 that the computer 105 can use to determine whether a specifictarget 200 will intersect or collide with the host vehicle 101.Specifically, the computer 105 may determine the acceleration threatnumber ATN, the brake threat number BTN, and the steering threat numberSTN for the host vehicle 101 and the target 200, and based on the threatnumbers ATN, BTN, STN, which may be combined into a single overallthreat number TN, actuate components 120 of the host vehicle 101. Thecomputer 105 can determine the threat number based on the origin O ofthe host vehicle 101 and the front center point 215 of the target 200.For example, the computer 105 can determine the threat number a centertime to collision, i.e., a predicted time to collision between the frontcenter point of the host vehicle 101 and the front center point 215 ofthe target 200.

The BTN is a measure of a needed longitudinal deceleration to allow thehost vehicle 101 to stop or reduce speed before colliding with thetarget 200. The BTN can be based on a measured host vehicle 101 speed, adistance between the target 200 and the host vehicle 101, and therespective projected trajectories of the target 200 and the host vehicle101. The computer 105 can determine a longitudinal deceleration to stopor reduce speed of the host vehicle 101 before colliding with the target200, e.g., 2 m/s². The computer 105 can determine a maximum decelerationof the host vehicle 101, e.g., 8 m/s². The BTN can be the ratio of theneeded deceleration to the maximum deceleration, e.g., BTN=2/8=0.25. Ifthe needed deceleration to avoid a collision with the target 200 exceedsthe maximum deceleration of the host vehicle 101, i.e., BTN>1, then thecomputer 105 can set the value of the BTN to 1, i.e., if BTN>1, BTN=1.

The STN is a measure of a needed lateral acceleration to allow the hostvehicle 101 to steer away from the target 200. As with the BTN, thecomputer 105 can determine a needed lateral acceleration to avoid acollision between the host vehicle 101 and the target 200. The STN canbe the ratio of the needed lateral acceleration to a maximum lateralacceleration of the host vehicle 101. If the needed lateral accelerationexceeds the maximum lateral acceleration, the computer 105 can set theSTN to 1.

The ATN is a measure of a needed longitudinal acceleration to allow thehost vehicle 101 to accelerate and pass the target 200. As describedabove for the BTN and the STN, the computer 105 can determine a neededacceleration to allow the host vehicle 101 to pass the target 200 and amaximum available acceleration of the host vehicle 101. The ATN can bethe ratio of the needed longitudinal acceleration to the maximumlongitudinal acceleration of the host vehicle 101. If the neededlongitudinal acceleration exceeds a maximum longitudinal acceleration,the computer 105 can set the ATN to 1. The computer 105 may determinethe STN, BTN, and/or ATN to produce a respective overall threat numberTN for the target 200.

The computer 105 can actuate one or more vehicle components 120 based onone of the threat numbers exceeding a predetermined threat threshold.The threat threshold can be determined based on, e.g., empirical testingof vehicles 101 in intersections, simulation modeling of vehicles 101,brake capacity, steering limits, etc. For example, if the overall threatnumber TN is above a threat threshold of 0.7, the computer 105 canactuate a brake 120 to decelerate the host vehicle 101, e.g., to −6.5meters per second squared (m/s²). In another example, if the threatnumber is above 0.4 but less than or equal to 0.7, the computer 105 canactuate the brake 120 to, e.g., a deceleration of −2.0 m/s². In anotherexample, if the threat number is greater than 0.2 but less than or equalto 0.4, the computer 105 can display a visual warning on a vehicle 101HMI and/or play an audio warning over a speaker.

FIG. 3 is a plan view of the host vehicle 101 and the target 200. Thecomputer 105 can identify a front corner point 300 of the target 200. Asused herein, a “corner point” is a point on the front bumper or the rearbumper of the target 200 substantially at the width w_(t), of the target200. That is, the longitudinal position of the bumpers of the target 200and width w_(t), can substantially define a rectangle having fourcorners. The coordinates of the four corners in the coordinate systemare the “corner points.” The computer 105 can determine a “front cornerpoint” 300 as one of the corner points at the front of the target 200,e.g., on the front bumper. The computer 105 can identify the frontcorner point as the closest corner point of the target 200 to the hostvehicle 101.

When the threat number exceeds the threshold, as described above, thecomputer 105 can determine whether the yaw rate {dot over (ψ)} is belowa predetermined threshold. Typically, turns require a greater yaw rate{dot over (ψ)} than curved roads and lane changes. To determine whetherthe vehicle 101 is performing a turn that can require collisionmitigation, the computer 105 can compare the yaw rate {dot over (ψ)} toa threshold. The threshold can be determined such that yaw rates {dotover (ψ)} below the threshold do not indicate that the vehicle 101 is ina turn. For example, the threshold can be determined based on a minimumyaw rate {dot over (ψ)} required for the vehicle 101 to complete aleft-hand turn from a roadway lane to a perpendicular roadway lane. Theminimum yaw rate {dot over (ψ)} can be determined with simulationmodeling of estimated yaw rates {dot over (ψ)} required for turns,curved roads, and lane changes. The simulation modeling can include aroadway lane for a simulated vehicle 101 and a perpendicular roadwaylane into which to turn. The simulation model can specify a yaw rate{dot over (ψ)} and determine whether the vehicle 101 entered theperpendicular roadway lane. The smallest yaw rate {dot over (ψ)} forwhich the simulated vehicle 101 turns into the perpendicular roadwaylane is the minimum yaw rate {dot over (ψ)} and can be the threshold.Alternatively, the threshold can be the minimum yaw rate {dot over (ψ)}multiplied by a safety factor, e.g., 1.5, 2.0, etc. If the yaw rate {dotover (ψ)} exceeds the threshold, the computer 105 can determine that thevehicle 101 is in a turn and can perform collision avoidance andmitigation based on the threat number. If the yaw rate {dot over (ψ)} isbelow the threshold, the computer 105 can determine that the vehicle 101may be in a false positive scenario that may not require collisionmitigation.

The computer 105 can determine a sign of the yaw rate {dot over (ψ)},i.e., whether the yaw rate {dot over (ψ)} is positive or negative. Inthe coordinate system shown in FIGS. 2 and 3, a positive yaw rate {dotover (ψ)} is counterclockwise, i.e., when the vehicle 101 turns left. Ina right-handed roadway lane, where vehicles 101 drive on the right sideof the road, a left-turning host vehicle 101 (having a positive yaw rate{dot over (ψ)}) will typically cross a roadway lane in which targets 200are moving toward the host vehicle 101. Thus, a positive yaw rate {dotover (ψ)} can indicate that the host vehicle 101 is in a left turn, anda negative yaw rate {dot over (ψ)} can indicate that the host vehicle101 is in a right turn that does not cross roadway lanes with oncomingtarget 200. That is, the computer 105 can determine whether the hostvehicle 101 is in a turn based on a sign of the yaw rate {dot over (ψ)}.The computer 105 can suppress threat mitigation when the sign of the yawrate {dot over (ψ)} is negative. Alternatively, in a left-handed roadwaylane, where vehicles 101 drive on the left side of the road, a positiveyaw rate {dot over (ψ)} (i.e., a left turn) can indicate that the hostvehicle 101 will not cross roadway lanes with oncoming targets 200, andthe computer 105 can suppress threat mitigation when the sign of the yawrate {dot over (ψ)} is positive.

Upon determining that the yaw rate {dot over (ψ)} is below thethreshold, the computer 105 can identify the front corner point 300 ofthe target 200 and determine a corner time to collision. As used herein,the “corner time to collision” is a predicted time until a collisionbetween the origin O and the front corner point 300 of the target 200.The computer 105 can determine the corner time to collision TTC_(corner)based on the range r and the range rate {dot over (r)}:

$\begin{matrix}{{TTC_{corner}} = \frac{r}{\overset{.}{r}}} & (1)\end{matrix}$

Based on the corner time to collision TTC_(corner), the computer 105 candetermine to suppress threat mitigation. When the corner time tocollision TTC_(corner) exceeds a time threshold, the computer 105 candetermine that the vehicle 101 will not collide with the front cornerpoint 300 of the target 200 and can suppress threat mitigation, e.g.,suppress actuation of a brake. The time threshold can be determinedbased on, e.g., empirical testing of a time required for the vehicle 101to clear the path of the target 200 during a turn. When the corner timeto collision TTC_(corner) exceeds the time threshold, the computer 105can determine that the vehicle 101, if in a turn, would complete theturn before the target 200 reaches the vehicle 101, and thus thecomputer 105 can determine to suppress threat mitigation. Alternatively,when the corner time to collision TTC_(corner) is below the timethreshold, the computer 105 can actuate one or more components 120 toavoid and/or mitigate a potential collision, e.g., the computer 105 canactuate a brake, a steering component, a throttle, etc.

To suppress threat mitigation, the computer 105 can determine a threatmultiplier. As used herein, the “threat multiplier” is a numerical valuethat is multiplied to the threat number to determine the overall threatnumber TN. For example, the threat multiplier may be 0 to indicate thatthe host vehicle 101 is not likely to collide with the target 200 evenwhen the threat number indicates otherwise. That is, the threatmultiplier can be a binary value of 0 or 1, where a threat multiplier of1 indicates that the computer 105 should continue with threat mitigationbased on the overall threat number TN and a threat multiplier of 0indicates that the vehicle 101 is in a false positive scenario and thecomputer 105 should not perform threat mitigation. Alternatively, thethreat multiplier may be a different number to account for theadditional or lower risk of collision based on data 115 about the frontcorner point 300 of the target 200, e.g., a number between 0 and 1. Thatis, the threat multiplier between 0 and 1 can adjust the overall threatnumber TN to more accurately assess the risk of collision. For example,the threat multiplier can reduce the overall threat number TN from above0.7 to below 0.7, and the computer 105 can, as described above, actuatecomponents 120 in a different manner when the overall threat number TNis below 0.7. When the computer 105 determines that the corner time tocollision TTC_(corner) is above the time threshold, the computer 105 canset the threat multiplier to 0. Thus, the computer 105 will not performthreat mitigation when the threat multiplier is 0.

FIG. 4 is a diagram of an example process 400 for operating a vehicle101. The process 400 begins in a block 405, in which a computer 105detects a target 200. The computer 105 can, based on data 115 collectedby sensors 110, detect a target 200 and determine e.g., a target lengthl_(tg), a target width w_(tg), a target speed, etc. Upon detecting thetarget 200, the computer 105 can determine whether a collision is likelybetween the target 200 and the host vehicle 101.

Next, in a block 410, the computer 105 determines a threat number basedon a front center point 215 of the target 200. As described above, thecomputer 105 can identify a point substantially at a center of a frontbumper of the target and can determine a threat number based on alikelihood of a collision between the host vehicle 101 and the frontcenter point 215. The threat number can be, e.g., an acceleration threatnumber ATN, a brake threat number BTN, a steering threat number STN,etc.

Next, in a block 415, the computer 105 determines whether the threatnumber exceeds a threshold. As described above, when the threat numberexceeds the threshold, the computer 105 can determine that the hostvehicle 101 is likely to collide with the target 200 absent threatmitigation. If the threat number exceeds the threshold, the process 400continues in a block 420. Otherwise, the process 400 continues in ablock 450.

In the block 420, the computer 105 determines a yaw rate {dot over (ψ)}of the host vehicle 101. As described above, the yaw rate {dot over (ψ)}is a measure of a change in a yaw angle ψ. The yaw rate {dot over (ψ)}can indicate whether the host vehicle 101 is turning toward aperpendicular roadway lane, performing a lane change, or on a curvedroadway.

Next, in a block 425, the computer 105 determines whether the yaw rate{dot over (ψ)} is below a threshold. The threshold can be determinedbased on, e.g., a minimum yaw rate {dot over (ψ)} required to perform aturn into a perpendicular roadway lane. The threshold can be determinedsuch that yaw rates {dot over (ψ)} below the threshold may not be aturn, e.g., a lane change, a curved road, etc. For example, as describedabove, the minimum yaw rate {dot over (ψ)} can be determined based on asimulation of a vehicle 101 turning from a roadway lane into aperpendicular roadway lane for a plurality of specified yaw rates {dotover (ψ)}. If the yaw rate {dot over (ψ)} is below the threshold, theprocess 400 continues in a block 430. Otherwise, the process 400continues in the block 450.

In the block 430, the computer 105 identifies a front corner point 300of the target 200. As described above, the front corner point 300 is apoint on the front bumper of the target 200 at the target width w_(tg).The computer 105 can identify the front corner point 300 as the closestcorner point to the origin O on the front bumper of the host vehicle101, i.e., the point on the target 200 that the host vehicle 101 willlikely contact first in a collision.

Next, in a block 435, the computer 105 determines a corner time tocollision TTC_(corner) between the host vehicle 101 and the front cornerpoint 300. As described above, the computer 105 can determine the cornertime to collision TTC_(corner) based on a range r and a range rate {dotover (r)} between the origin O on the host vehicle 101 and the frontcorner point 300.

Next, in a block 440, the computer 105 determines whether the cornertime to collision TTC_(corner) exceeds a time threshold. The timethreshold can be, e.g., an average time for the host vehicle 101 tocomplete the turn into the perpendicular roadway lane. If the cornertime to collision TTC_(corner) exceeds the time threshold, the process400 continues in a block 445. Otherwise, the process 400 continues inthe block 450.

In the block 445, the computer 105 suppresses threat mitigation. Asdescribed above, the computer 105 can determine that a collision withthe target 200 is not likely because, e.g., the host vehicle 101 is notin a turn but rather is performing a lane change or is on a curvedroadway. The computer 105 can set a threat multiplier to 0 and multiplythe threat number by the threat multiplier. Because the multipliedthreat number is 0, the computer 105 does not perform further actions toprevent or mitigate a collision between the host vehicle 101 and thetarget.

In the block 450, the computer 105 determines whether to continue theprocess 400. For example, the computer 105 can determine to continue theprocess 400 if the vehicle 101 is still operating on a route. In anotherexample, the computer 105 can determine not to continue the process 400if the vehicle 101 is stopped and powered off, e.g., when parked. If thecomputer 105 determines to continue, the process 400 returns to theblock 405 to detect another target 200. Otherwise, the process 400 ends.

As used herein, the adverb “substantially” modifying an adjective meansthat a shape, structure, measurement, value, calculation, etc. maydeviate from an exact described geometry, distance, measurement, value,calculation, etc., because of imperfections in materials, machining,manufacturing, data collector measurements, computations, processingtime, communications time, etc.

Computing devices discussed herein, including the computer 105 andserver 130 include processors and memories, the memories generally eachincluding instructions executable by one or more computing devices suchas those identified above, and for carrying out blocks or steps ofprocesses described above. Computer executable instructions may becompiled or interpreted from computer programs created using a varietyof programming languages and/or technologies, including, withoutlimitation, and either alone or in combination, Java™, C, C++, VisualBasic, Java Script, Perl, HTML, etc. In general, a processor (e.g., amicroprocessor) receives instructions, e.g., from a memory, a computerreadable medium, etc., and executes these instructions, therebyperforming one or more processes, including one or more of the processesdescribed herein. Such instructions and other data may be stored andtransmitted using a variety of computer readable media. A file in thecomputer 105 is generally a collection of data stored on a computerreadable medium, such as a storage medium, a random access memory, etc.

A computer readable medium includes any medium that participates inproviding data (e.g., instructions), which may be read by a computer.Such a medium may take many forms, including, but not limited to, nonvolatile media, volatile media, etc. Non volatile media include, forexample, optical or magnetic disks and other persistent memory. Volatilemedia include dynamic random access memory (DRAM), which typicallyconstitutes a main memory. Common forms of computer readable mediainclude, for example, a floppy disk, a flexible disk, hard disk,magnetic tape, any other magnetic medium, a CD ROM, DVD, any otheroptical medium, punch cards, paper tape, any other physical medium withpatterns of holes, a RAM, a PROM, an EPROM, a FLASH EEPROM, any othermemory chip or cartridge, or any other medium from which a computer canread.

With regard to the media, processes, systems, methods, etc. describedherein, it should be understood that, although the steps of suchprocesses, etc. have been described as occurring according to a certainordered sequence, such processes could be practiced with the describedsteps performed in an order other than the order described herein. Itfurther should be understood that certain steps could be performedsimultaneously, that other steps could be added, or that certain stepsdescribed herein could be omitted. For example, in the process 500, oneor more of the steps could be omitted, or the steps could be executed ina different order than shown in FIG. 5. In other words, the descriptionsof systems and/or processes herein are provided for the purpose ofillustrating certain embodiments, and should in no way be construed soas to limit the disclosed subject matter.

Accordingly, it is to be understood that the present disclosure,including the above description and the accompanying figures and belowclaims, is intended to be illustrative and not restrictive. Manyembodiments and applications other than the examples provided would beapparent to those of skill in the art upon reading the abovedescription. The scope of the invention should be determined, not withreference to the above description, but should instead be determinedwith reference to claims appended hereto and/or included in a nonprovisional patent application based hereon, along with the full scopeof equivalents to which such claims are entitled. It is anticipated andintended that future developments will occur in the arts discussedherein, and that the disclosed systems and methods will be incorporatedinto such future embodiments. In sum, it should be understood that thedisclosed subject matter is capable of modification and variation.

The article “a” modifying a noun should be understood as meaning one ormore unless stated otherwise, or context requires otherwise. The phrase“based on” encompasses being partly or entirely based on.

What is claimed is:
 1. A system, comprising a computer including aprocessor and a memory, the memory storing instructions executable bythe processor to: upon determining that a yaw rate for a host vehicle isbelow a threshold, identify a front corner point of a target; andsuppress threat mitigation when a time to collision between the hostvehicle and front corner point of the target exceeds a time threshold.2. The system of claim 1, wherein the instructions further includeinstructions to identify the front corner point as a closest cornerpoint of the target to the host vehicle.
 3. The system of claim 1,wherein the instructions further include instructions to determine thetime to collision between a front center point of the host vehicle andthe front corner point of the target.
 4. The system of claim 1, whereinthe instructions further include instructions to determine a threatnumber based on a front center point of the host vehicle and a frontcenter point of the target.
 5. The system of claim 4, wherein theinstructions further include instructions to determine the threat numberbased on a center time to collision between the front center point ofthe host vehicle and the front center point of the target.
 6. The systemof claim 4, wherein the instructions further include instructions toactuate a component based on a threat number.
 7. The system of claim 4,wherein the instructions further include instructions to, upondetermining that the threat number exceeds a threat threshold, determinewhether the yaw rate is below the threshold.
 8. The system of claim 4,wherein the instructions further include instructions to multiply athreat multiplier to the threat number to suppress the threatmitigation.
 9. The system of claim 8, wherein the instructions furtherinclude instructions to set the threat multiplier to zero when the timeto collision exceeds the time threshold.
 10. The system of claim 1,wherein the instructions further include instructions to actuate a brakewhen the time to collision is below the time threshold.
 11. The systemof claim 1, wherein the instructions further include instructions toidentify the front corner point of the target based on a lateral widthof the target.
 12. The system of claim 1, wherein the instructions tosuppress threat mitigation further include instructions to suppressactuation of a brake.
 13. The system of claim 1, wherein theinstructions further include instructions to determine whether the hostvehicle is in a turn based on a sign of the yaw rate.
 14. The system ofclaim 13, wherein the instructions further include instructions tosuppress threat mitigation when the sign of the yaw rate is negative.15. A method, comprising: upon determining that a yaw rate for a hostvehicle is below a threshold, identifying a front corner point of atarget; and suppressing threat mitigation when a time to collisionbetween the host vehicle and front corner point of the target exceeds atime threshold.
 16. The method of claim 15, further comprisingdetermining the time to collision between a front center point of thehost vehicle and the front corner point of the target.
 17. The method ofclaim 15, further comprising determining a threat number based on afront center point of the host vehicle and a front center point of thetarget.
 18. A system, comprising: a brake in a host vehicle; means foridentifying a front corner point of a target upon determining that a yawrate for the host vehicle is below a threshold; and means forsuppressing the brake when a time to collision between the host vehicleand front corner point of the target exceeds a time threshold.
 19. Thesystem of claim 18, further comprising means for determining the time tocollision between a front center point of the host vehicle and the frontcorner point of the target.
 20. The system of claim 18, furthercomprising means for determining a threat number based on a front centerpoint of the host vehicle and a front center point of the target.